{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Download any OSM Geospatial Entities with OSMnx\n",
    "\n",
    "Author: [Geoff Boeing](https://geoffboeing.com/)\n",
    "\n",
    "More info:\n",
    "\n",
    "  - [Overview of OSMnx](http://geoffboeing.com/2016/11/osmnx-python-street-networks/)\n",
    "  - [Documentation and install instructions](https://osmnx.readthedocs.io)\n",
    "  - [Examples, demos, tutorials](https://github.com/gboeing/osmnx-examples)\n",
    "  - [Journal article and citation info](http://geoffboeing.com/publications/osmnx-complex-street-networks/)\n",
    "  - [GitHub repo](https://github.com/gboeing/osmnx)\n",
    "  \n",
    "This notebook provides a quick tour of using OSMnx to download any geospatial entites/objects from OpenStreetMap as a geopandas GeoDataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1.0.0'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import osmnx as ox\n",
    "%matplotlib inline\n",
    "ox.config(log_console=True)\n",
    "ox.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use the `geometries` module to download entities, such as grocery stores, transit stops, points of interest, or building footprints, and turn them into a GeoDataFrame: [see docs](https://osmnx.readthedocs.io/en/stable/osmnx.html#module-osmnx.geometries).\n",
    "\n",
    "To query, pass a `tags` dict where keys are OSM tags. The dict's values can be either:\n",
    "  1. `True` to retrieve all OSM objects with this tag, regardless of its value\n",
    "  2. a single value as a string to retrieve all OSM objects with this tag:value combination\n",
    "  3. a list of string values to retrieve all OSM objects where this tag matches any of these values\n",
    "\n",
    "Pass multiple dict key:value pairs to retrieve the union (not intersection) of these pairs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(50, 45)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get all building footprints in some neighborhood\n",
    "# `True` means retrieve any object with this tag, regardless of value\n",
    "place = 'Bunker Hill, Los Angeles, California'\n",
    "tags = {'building': True}\n",
    "gdf = ox.geometries_from_place(place, tags)\n",
    "gdf.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 216x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = ox.plot_footprints(gdf, figsize=(3, 3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4, 8)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get all the parks in some neighborhood\n",
    "# constrain acceptable `leisure` tag values to `park`\n",
    "tags = {'leisure': 'park'}\n",
    "gdf = ox.geometries_from_place(place, tags)\n",
    "gdf.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(98, 43)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get everything tagged amenity,\n",
    "# and everything tagged landuse = retail or commercial,\n",
    "# and everything tagged highway = bus_stop\n",
    "tags = {'amenity' : True,\n",
    "        'landuse' : ['retail', 'commercial'],\n",
    "        'highway' : 'bus_stop'}\n",
    "gdf = ox.geometries_from_place('Piedmont, California, USA', tags)\n",
    "gdf.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>unique_id</th>\n",
       "      <th>osmid</th>\n",
       "      <th>element_type</th>\n",
       "      <th>amenity</th>\n",
       "      <th>name</th>\n",
       "      <th>geometry</th>\n",
       "      <th>brand</th>\n",
       "      <th>brand:wikidata</th>\n",
       "      <th>brand:wikipedia</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>node/2810181540</td>\n",
       "      <td>2810181540</td>\n",
       "      <td>node</td>\n",
       "      <td>bank</td>\n",
       "      <td>Citibank</td>\n",
       "      <td>POINT (-122.23256 37.82515)</td>\n",
       "      <td>Citibank</td>\n",
       "      <td>Q857063</td>\n",
       "      <td>en:Citibank</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>way/276424028</td>\n",
       "      <td>276424028</td>\n",
       "      <td>way</td>\n",
       "      <td>bank</td>\n",
       "      <td>Bank of America</td>\n",
       "      <td>POLYGON ((-122.23258 37.82491, -122.23252 37.8...</td>\n",
       "      <td>Bank of America</td>\n",
       "      <td>Q487907</td>\n",
       "      <td>en:Bank of America</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>way/285549437</td>\n",
       "      <td>285549437</td>\n",
       "      <td>way</td>\n",
       "      <td>bank</td>\n",
       "      <td>Wells Fargo</td>\n",
       "      <td>POLYGON ((-122.23147 37.82466, -122.23134 37.8...</td>\n",
       "      <td>Wells Fargo</td>\n",
       "      <td>Q744149</td>\n",
       "      <td>en:Wells Fargo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          unique_id       osmid element_type amenity             name  \\\n",
       "7   node/2810181540  2810181540         node    bank         Citibank   \n",
       "86    way/276424028   276424028          way    bank  Bank of America   \n",
       "89    way/285549437   285549437          way    bank      Wells Fargo   \n",
       "\n",
       "                                             geometry            brand  \\\n",
       "7                         POINT (-122.23256 37.82515)         Citibank   \n",
       "86  POLYGON ((-122.23258 37.82491, -122.23252 37.8...  Bank of America   \n",
       "89  POLYGON ((-122.23147 37.82466, -122.23134 37.8...      Wells Fargo   \n",
       "\n",
       "   brand:wikidata     brand:wikipedia  \n",
       "7         Q857063         en:Citibank  \n",
       "86        Q487907  en:Bank of America  \n",
       "89        Q744149      en:Wells Fargo  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# view just the banks\n",
    "gdf[gdf['amenity']=='bank'].dropna(axis=1, how='any')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>unique_id</th>\n",
       "      <th>osmid</th>\n",
       "      <th>element_type</th>\n",
       "      <th>name</th>\n",
       "      <th>geometry</th>\n",
       "      <th>bus</th>\n",
       "      <th>highway</th>\n",
       "      <th>network</th>\n",
       "      <th>public_transport</th>\n",
       "      <th>ref</th>\n",
       "      <th>route_ref</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>node/4071030440</td>\n",
       "      <td>4071030440</td>\n",
       "      <td>node</td>\n",
       "      <td>Park Boulevard &amp; Saint James Drive</td>\n",
       "      <td>POINT (-122.21517 37.81248)</td>\n",
       "      <td>yes</td>\n",
       "      <td>bus_stop</td>\n",
       "      <td>AC Transit</td>\n",
       "      <td>platform</td>\n",
       "      <td>57544</td>\n",
       "      <td>V;33;688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>node/5844909127</td>\n",
       "      <td>5844909127</td>\n",
       "      <td>node</td>\n",
       "      <td>Park Boulevard &amp; Estates Drive</td>\n",
       "      <td>POINT (-122.21392 37.81363)</td>\n",
       "      <td>yes</td>\n",
       "      <td>bus_stop</td>\n",
       "      <td>AC Transit</td>\n",
       "      <td>platform</td>\n",
       "      <td>54866</td>\n",
       "      <td>V;33;688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>node/5845148873</td>\n",
       "      <td>5845148873</td>\n",
       "      <td>node</td>\n",
       "      <td>Hampton Road &amp; Sandringham Road</td>\n",
       "      <td>POINT (-122.21492 37.81822)</td>\n",
       "      <td>yes</td>\n",
       "      <td>bus_stop</td>\n",
       "      <td>AC Transit</td>\n",
       "      <td>platform</td>\n",
       "      <td>53832</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>node/5845152990</td>\n",
       "      <td>5845152990</td>\n",
       "      <td>node</td>\n",
       "      <td>Hampton Road &amp; Sandringham Road</td>\n",
       "      <td>POINT (-122.21459 37.81818)</td>\n",
       "      <td>yes</td>\n",
       "      <td>bus_stop</td>\n",
       "      <td>AC Transit</td>\n",
       "      <td>platform</td>\n",
       "      <td>50830</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>node/5845153014</td>\n",
       "      <td>5845153014</td>\n",
       "      <td>node</td>\n",
       "      <td>Hampton Road &amp; Seaview Avenue</td>\n",
       "      <td>POINT (-122.22303 37.81763)</td>\n",
       "      <td>yes</td>\n",
       "      <td>bus_stop</td>\n",
       "      <td>AC Transit</td>\n",
       "      <td>platform</td>\n",
       "      <td>53865</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          unique_id       osmid element_type  \\\n",
       "10  node/4071030440  4071030440         node   \n",
       "13  node/5844909127  5844909127         node   \n",
       "14  node/5845148873  5845148873         node   \n",
       "15  node/5845152990  5845152990         node   \n",
       "16  node/5845153014  5845153014         node   \n",
       "\n",
       "                                  name                     geometry  bus  \\\n",
       "10  Park Boulevard & Saint James Drive  POINT (-122.21517 37.81248)  yes   \n",
       "13      Park Boulevard & Estates Drive  POINT (-122.21392 37.81363)  yes   \n",
       "14     Hampton Road & Sandringham Road  POINT (-122.21492 37.81822)  yes   \n",
       "15     Hampton Road & Sandringham Road  POINT (-122.21459 37.81818)  yes   \n",
       "16       Hampton Road & Seaview Avenue  POINT (-122.22303 37.81763)  yes   \n",
       "\n",
       "     highway     network public_transport    ref route_ref  \n",
       "10  bus_stop  AC Transit         platform  57544  V;33;688  \n",
       "13  bus_stop  AC Transit         platform  54866  V;33;688  \n",
       "14  bus_stop  AC Transit         platform  53832        33  \n",
       "15  bus_stop  AC Transit         platform  50830        33  \n",
       "16  bus_stop  AC Transit         platform  53865        33  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# view just the bus stops\n",
    "gdf[gdf['highway']=='bus_stop'].dropna(axis=1, how='any').head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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